With newly rising coronavirus disease 2019 (COVID-19) cases, important data gaps remain on (i) long-term dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates in fixed cohorts (ii) identification of risk factors, and (iii) establishment of effective surveillance strategies. By polymerase chain reaction and antibody testing of 1% of the local population and >90,000 app-based datasets, the present study surveilled a catchment area of 300,000 inhabitants from March 2020 to February 2021. Cohort (56% female; mean age, 45.6 years) retention was 75 to 98%. Increased risk for seropositivity was detected in several high-exposure groups, especially nurses. Unreported infections dropped from 92 to 29% during the study. "Contact to COVID-19-affected" was the strongest risk factor, whereas public transportation, having children in school, or tourism did not affect infection rates. With the first SARS-CoV-2 cohort study, we provide a transferable model for effective surveillance, enabling monitoring of reinfection rates and increased preparedness for future pandemics.

Original languageEnglish
Article numbereabm5016
JournalScience Advances
Issue number15
Publication statusPublished - 15.04.2022

Research Areas and Centers

  • Academic Focus: Center for Infection and Inflammation Research (ZIEL)
  • Research Area: Center for Population Medicine and Public Health (ZBV)

DFG Research Classification Scheme

  • 204-05 Immunology
  • 205-02 Public Health, Health Services Research and Social Medicine

Coronavirus related work

  • Research on SARS-CoV-2 / COVID-19


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